Run
2041959

Run 2041959

Task 15 (Supervised Classification) breast-w Uploaded 15-04-2017 by Jeroen van Hoof
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  • NumPy_1.12.0. Python_3.6.0. run_task Sat_Apr_15_20.32.30_2017 SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,onehot encoder=sklearn.preprocessing.data.OneHotEncoder,randomforestclassifier=skl earn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrapTrue
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weightNone
sklearn.ensemble.forest.RandomForestClassifier(16)_criteriongini
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depth3
sklearn.ensemble.forest.RandomForestClassifier(16)_max_features0.05
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodesNone
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split18
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators300
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs-1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_scoreFalse
sklearn.ensemble.forest.RandomForestClassifier(16)_random_state3
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_startFalse
sklearn.preprocessing.data.OneHotEncoder(3)_categorical_features[False, False, False, False, False, False, False, False, False]
sklearn.preprocessing.data.OneHotEncoder(3)_dtype
sklearn.preprocessing.data.OneHotEncoder(3)_handle_unknownignore
sklearn.preprocessing.data.OneHotEncoder(3)_n_valuesauto
sklearn.preprocessing.data.OneHotEncoder(3)_sparseFalse
sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps[('dualimputer', ), ('onehotencoder', OneHotEncoder(categorical_features=[False, False, False, False, False, False, False, False, False], dtype=, handle_unknown='ignore', n_values='auto', sparse=False)), ('randomforestclassifier', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini', max_depth=3, max_features=0.050000000000000003, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=2, min_samples_split=18, min_weight_fraction_leaf=0.0, n_estimators=300, n_jobs=-1, oob_score=False, random_state=3, verbose=0, warm_start=False))]

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

0.9908
Per class
Cross-validation details (10-fold Crossvalidation)
0.9729
Per class
Cross-validation details (10-fold Crossvalidation)
0.9404
Cross-validation details (10-fold Crossvalidation)
568.0292
Cross-validation details (10-fold Crossvalidation)
0.0988
Cross-validation details (10-fold Crossvalidation)
0.452
Cross-validation details (10-fold Crossvalidation)
699
Per class
Cross-validation details (10-fold Crossvalidation)
0.9734
Per class
Cross-validation details (10-fold Crossvalidation)
0.9728
Cross-validation details (10-fold Crossvalidation)
0.9297
Cross-validation details (10-fold Crossvalidation)
0.9728
Per class
Cross-validation details (10-fold Crossvalidation)
0.2185
Cross-validation details (10-fold Crossvalidation)
0.4753
Cross-validation details (10-fold Crossvalidation)
0.1762
Cross-validation details (10-fold Crossvalidation)
0.3706
Cross-validation details (10-fold Crossvalidation)